Cost-Utility Analysis of Ligament Reconstruction Tendon Interposition Versus Suture Suspension Arthroplasty for Thumb Osteoarthritis
Bibliographic record
Abstract
Background: Thumb carpometacarpal joint osteoarthritis (CMCJ OA) is a common degenerative condition that causes pain, stiffness, and disability, reducing quality of life. Surgery is a well-established treatment option when conservative management fails, but the optimal surgical approach remains debated. This study compared the cost-utility of trapeziectomy with ligament reconstruction and tendon interposition (LRTI + T) versus suture suspension arthroplasty (SSA) for CMCJ OA. Methods: A Markov microsimulation model was developed to compare LRTI + T and SSA from a hospital payer perspective. Outcomes included incremental cost-effectiveness ratio, quality-adjusted life years (QALYs), total cost, and net monetary benefit. Clinical outcomes such as complication rates and revision surgery were also evaluated. Results: LRTI + T had a higher complication rate (14.6%) than SSA (9.8%), but SSA had a slightly higher revision rate (7.1% versus 5.7%). Over a lifetime, SSA provided an incremental gain of 0.25 QALYs but was marginally more expensive ($2855 versus $2842). SSA yielded an incremental cost-effectiveness ratio of $53.80 per QALY, making it the more cost-effective strategy. Conclusions: SSA is a cost-effective alternative to LRTI + T, offering valuable insights for clinicians and policymakers optimizing care for CMCJ OA patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".